Graphical Abstract:

Abstract:

Background: The role of adipose tissue in Insulin resistance (IR) and Type 2 Diabetes
(T2D) has well been received in the biomedical community; being a precursor of T2D, identification
of the molecular basis of IR is therefore, vital to elucidate T2D- pathogenesis and meta-analysis of
previously conducted microarray studies provides an inexpensive approach to achieve this end.

Methods: In this study, we have carried out a statistical meta-analysis of 157 microarray datasets from
five independent studies and identified a meta-signature of 1,511 genes; their functional meaning was
elucidated by integrated pathways-analysis. Further, a protein-protein interaction network was constructed
and key genes along with their high confidence transcriptional- and epigenetic-mediators
were identified using a network biology approach.

Results: Various inflammation- and immune system-related pathways such as TGF-β signaling, IL7
signaling, Neutrophil degranulation, and Chemokine signaling etc. were enriched in sick adipose tissues;
identified transcription factors, and microRNAs were also found to regulate processes relevant to
IR/T2D pathophysiology.

Conclusion: This study endorses the development of effective bioinformatics workflow and further
grants an indication for the acceptance of adiposopathy as the root mechanistic pathology that poses
risk for development of type 2 diabetes; concept of adipospathy in place of metabolic syndrome will
open the possibility to design drugs, those will ameliorate adipose functions and hence proved to be
more effective against Type 2 Diabetes.

Abstract:Background: The role of adipose tissue in Insulin resistance (IR) and Type 2 Diabetes
(T2D) has well been received in the biomedical community; being a precursor of T2D, identification
of the molecular basis of IR is therefore, vital to elucidate T2D- pathogenesis and meta-analysis of
previously conducted microarray studies provides an inexpensive approach to achieve this end.

Methods: In this study, we have carried out a statistical meta-analysis of 157 microarray datasets from
five independent studies and identified a meta-signature of 1,511 genes; their functional meaning was
elucidated by integrated pathways-analysis. Further, a protein-protein interaction network was constructed
and key genes along with their high confidence transcriptional- and epigenetic-mediators
were identified using a network biology approach.

Results: Various inflammation- and immune system-related pathways such as TGF-β signaling, IL7
signaling, Neutrophil degranulation, and Chemokine signaling etc. were enriched in sick adipose tissues;
identified transcription factors, and microRNAs were also found to regulate processes relevant to
IR/T2D pathophysiology.

Conclusion: This study endorses the development of effective bioinformatics workflow and further
grants an indication for the acceptance of adiposopathy as the root mechanistic pathology that poses
risk for development of type 2 diabetes; concept of adipospathy in place of metabolic syndrome will
open the possibility to design drugs, those will ameliorate adipose functions and hence proved to be
more effective against Type 2 Diabetes.